There are many kinds of electrical and electronic devices that are widely available for scientific, business, and consumer-oriented applications. Rapid advances in technology have allowed their use to migrate from universities and large institutions to small businesses and homes. Computers are now popular, even for use by children, and a myriad of different telephones, televisions, games and gadgets may now be found in almost every household in the country. The new technology has not only made such applications possible, but has also lowered the cost of electronic devices to the point where they can be produced in great numbers and are easily affordable.
A great many components used in building electronic products are currently mass-produced despite the fact that their successful manufacture depends on fabrication to extremely precise tolerances. Semiconductor wafers, for example, and the printed circuit boards on which they are mounted, require the formation of a huge number of very small surface structures. These structures are often formed automatically using mechanical or chemical means, that is, without direct human intervention. In the case of, for example, semiconductor wafers, these structures are formed by alternately removing select portions of a silicon substrate and applying additional materials or treating with chemical substances to produce surface structures having desirable properties. These structures are often so small that they can barely be seen, if at all, with the naked eye.
In one manufacturing operation, a material called photoresist (or simply “resist”) is applied to the surface of a wafer that is being used to make semiconductor chips. FIG. 1 is an illustration of an exemplary wafer 100, shown in plan view. The wafer 100 is divided into a number of dice, for example die 105. The wafer 100 forms a flat edge (or simply “flat”) 110 that may be used as a reference for locating specific points or dice, such as center point 115 or die 105. Resist may be deposited at center point 115 and the wafer 100 spun to evenly distribute the resist over its surface 101.
When the resist has been spread over the surface, it is selectively exposed to light emitted through a mask to create a pattern. The light causes changes in the resist so that when the surface is later rinsed, some of the resist will be washed away and some will remain. This forms a series of structures on surface 101 of wafer 100 (see FIG. 2). The wafer can then be treated, for example with a solution that etches away portions of the surface not covered with resist. Or additional materials may be deposited in similar fashion. This process is repeated until the desired components have been created on the surface of the wafer. It should be apparent that the structures made of resist or of other materials must be correctly formed onto the surface for the production process to create properly-functioning components. FIG. 2 is a side view of a small portion of wafer 100, illustrating the presence of a number of structures formed on surface 101. Although FIG. 2 is a cutaway view, it is only for illustration and not intended to represent any specific section of wafer 100. In addition, the actual size and location of structures 120, 121, and 122 are dependent on the specific application and their purpose in the production process. these structures may be formed of developed resist, or of materials deposited in the surface 101, or formed as a result of an etching process.
Because these surface structures are sometimes created in a series of reversible steps, identifying defects early may mean that corrective measures can be taken. And ultimately, finished products require inspection so that defective ones are not used. In the case of products such as semiconductor wafers, which frequently are used to for a number of separate components, portions identified as defective can be discarded while non-defective portions can be saved for eventual packaging and use. When production is finished (to an appropriate stage), the dice are separated and each individual die (along with a number of leads for providing electrical connections) is encapsulated in plastic to form a chip (not shown). Once manufactured, the chip will be programmed to perform one or more of the many functions for which they are used in electronic devices.
As should be apparent, a wafer therefore must undergo a fairly-large number of manufacturing steps before it is completed. During manufacturing, it also undergoes a corresponding number of test and inspections of various types. Although humans can and do inspect such products during the manufacturing process, often with the aid of a microscope or similar device, automated inspection systems are frequently desirable because they can perform the inspection much faster and, in some cases, more reliably. Optical inspection systems may be used in this role. Optical inspection systems, in general, capture images of the object being inspected after the object's surface has been illuminated by some form of light energy. The images may be examined by operators, and for this purpose may undergo some form of enhancement. Captured images, however, are often converted into digitized form for computer analysis.
This analysis may be done in a variety of ways. The images in digitized form may also be stored for future reference or converted back into a human-readable visual image. In general, computer analysis of captured images relies on the relative characteristics associated with each of a number of picture elements, or pixels. These pixels may be separately evaluated because they each represent the light received and converted into an electrical charge by one of many small photo-sensitive devices that are housed within a camera. To create a visual image, the data collected in this way by each of these individual pixels is aggregated to create a picture. Computer analysis is more flexible, because it can evaluate the pixel data more precisely and in a variety of ways. The captured image of a semiconductor wafer being evaluated may, for example, be compared to a previously-captured image of a ‘perfect’ wafer (which may have been generated by a computer rather than captured with a camera). Instead of the so-called golden-image comparison, some systems employ a die-to-die or frame-to-frame comparison. In these types of analyses, defective areas are identified simply because they deviate from other areas of the wafer that should yield a nearly-identical image.
Although other inspection methods may be employed, optical inspection has become very popular in electronics manufacturing operations and is widely used. Existing systems are far from perfect, however. For example, all optical imaging systems are limited in resolution by fundamental optical principles related to the wavelength of light, numerical aperture of the apparatus used, and by the overall geometry of the system. As components decrease in size, inspection tools are continually pushed to identify defects at or below their optimum optical resolution. In addition, even in an inspection process that simply compares a newly-captured image against a theoretically perfect reference, random variations can lead to noise sources in both the reference and newly acquired image thus leading to an overall reduction in defect detection sensitivity.
In addition, the analytical approach used is typically applied individually as the specific configuration and setup of hardware, software, and design strategy permits. Each of the defect detection schemes in current usage has its own strengths and weaknesses, and, depending on the defect signature, applicability. As a consequence, these approaches must often utilize complex filtering schemes in an attempt to reduce erroneous defects, sometimes at the expense of overall system resolution.
Needed then, is a methodology for more efficiently performing automated defect detection that provides greater statistical confidence in the result but does not greatly reduce system resolution. The present invention provides just such a solution.